Remove Business Intelligence Remove Data Lake Remove Data Workflow Remove Raw Data
article thumbnail

Data Engineering Zoomcamp – Data Ingestion (Week 2)

Hepta Analytics

This week, we got to think about our data ingestion design. We looked at the following: How do we ingest – ETL vs ELT Where do we store the dataData lake vs data warehouse Which tool to we use to ingest – cronjob vs workflow engine NOTE : This weeks task requires good internet speed and good compute.

article thumbnail

A Complete Guide to Azure Data Engineer Certification (DP-203)

Knowledge Hut

The Azure Data Engineer certification imparts to them a deep understanding of data processing, storage and architecture. By leveraging their proficiency, they enable organizations to transform raw data into valuable insights that drive business decisions. What is the Azure Data Engineer Certification?

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

New Fivetran connector streamlines data workflows for real-time insights

ThoughtSpot

The pathway from ETL to actionable analytics can often feel disconnected and cumbersome, leading to frustration for data teams and long wait times for business users. And even when we manage to streamline the data workflow, those insights aren’t always accessible to users unfamiliar with antiquated business intelligence tools.

article thumbnail

Build vs Buy Data Pipeline Guide

Monte Carlo

While we won’t get into the minutia of every consideration for every level of the data stack, it’s important to recall these five considerations as they’ll nonetheless steer the direction of our conversation. Data ingestion When we think about the flow of data in a pipeline, data ingestion is where the data first enters our platform.

article thumbnail

Data Pipeline Architecture Explained: 6 Diagrams and Best Practices

Monte Carlo

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. Zero ETL is a bit of a misnomer.

article thumbnail

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59